CN111325367B - Test time prediction system and method thereof - Google Patents
Test time prediction system and method thereof Download PDFInfo
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- CN111325367B CN111325367B CN201811523881.XA CN201811523881A CN111325367B CN 111325367 B CN111325367 B CN 111325367B CN 201811523881 A CN201811523881 A CN 201811523881A CN 111325367 B CN111325367 B CN 111325367B
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Abstract
The invention provides a test time prediction system and a method thereof. After the receiving module receives a test script comprising a plurality of current test items, the processing module compares the similarity of each current test item with each historical test item stored in the test database, and evaluates the test time corresponding to the historical test item with the highest similarity as the estimated time of the current test item. The evaluation module evaluates the time spent by the test tool loaded to the corresponding current tester model in each current test item. The output module sums the estimated time of each current test item and the time spent by each test tool to load to the corresponding current test machine model to output the predicted test time of the corresponding test script.
Description
Technical Field
The present invention relates to a prediction system and a method thereof, and more particularly, to a test time prediction system and a method thereof.
Background
After a customer places an order for a company, the company's production management will decide which product to offer to the customer at which point in time from which production line based on the customer's needs. The production line is arranged after ordering and before delivery, the machine testing time occupies a large proportion of the whole production period, the machine testing time is roughly estimated manually by self experience at present, but the error is large, and the condition that delivery waits for the completion of the test or delivery waits after the completion of the test is easily generated.
In summary, it is known that in the prior art, due to the fact that the machine testing time is estimated based on experience, the situation of waiting for the delivery to be tested or waiting for the delivery after the testing is completed is easily generated, and therefore, it is necessary to provide an improved technical means to solve the problem.
Disclosure of Invention
The invention provides a test time prediction system and a method thereof.
First, the present invention discloses a test time prediction system, which comprises: the device comprises a receiving module, a test database, a processing module, an evaluation module and an output module. The receiving module is used for receiving a test script, wherein the test script comprises a plurality of current test items, and each current test item comprises a current test machine model and a corresponding test tool. The test database is used for storing a plurality of historical test items and corresponding test time according to a test completion sequence, wherein each historical test item comprises a historical test machine model. The processing module is used for comparing the similarity of the current test machine type included by each current test item with the similarity of the historical test machine types included by each historical test item, and evaluating the test time corresponding to the historical test machine type with the highest similarity with a certain current test machine type as the estimated time of the current test item including the current test machine type. The evaluation module is used for evaluating the time spent by each test tool to load to the corresponding current test machine model according to the speed of the network and the size of each test tool. The output module is used for summing the estimated time of each current test item and the time spent by each test tool to load to the corresponding current test machine model so as to output the predicted test time of the corresponding test script.
In addition, the invention discloses a test time prediction method, which comprises the following steps: providing a test time prediction system which comprises a receiving module, a test database, a processing module, an evaluation module and an output module; the test database stores a plurality of historical test items and corresponding test time according to a test completion sequence, wherein each historical test item comprises a historical test machine model; the method comprises the steps that a receiving module receives a test script, wherein the test script comprises a plurality of current test items, and each current test item comprises a current test machine type and a corresponding test tool; the processing module compares the similarity of the current testing machine type included by each current testing item with the similarity of the historical testing machine type included by each historical testing item; the processing module evaluates the test time corresponding to the historical test machine model with the highest similarity to a current test machine model as the estimated time of the current test item including the current test machine model; the evaluation module evaluates the time spent by each test tool to load to the corresponding current test machine model according to the speed of the network and the size of each test tool; and the output module sums the estimated time of each current test item and the time spent by each test tool to load to the corresponding current test machine model so as to output the predicted test time of the corresponding test script.
The system and the method disclosed by the invention have the difference from the prior art that the similarity comparison is carried out on each current test item and each historical test item stored in the test database through the processing module so as to evaluate the estimated time of each current test item; the evaluation module evaluates the time spent by loading the test tool in each current test item to the corresponding current test machine model; and the output module sums the estimated time of each current test item and the time spent by each test tool to load to the corresponding current test machine model so as to output the predicted test time of the corresponding test script.
By the technical means, the invention can realize intelligent prediction of the test time and provide relatively accurate test finishing time in real time, thereby improving the efficiency and saving the cost.
Drawings
FIG. 1 is a system block diagram of an embodiment of a test time prediction system of the present invention.
FIG. 2 is a flowchart of a method of the test time prediction system of FIG. 1 for performing an embodiment of the test time prediction method.
Description of the symbols:
100. test time prediction system
110. Receiving module
120. Test database
130. Processing module
140. Evaluation module
150. Output module
Detailed Description
The following detailed description of the embodiments of the present invention will be provided in conjunction with the accompanying drawings and examples, so that how to implement the technical means for solving the technical problems and achieving the technical effects of the present invention can be fully understood and implemented.
Referring to fig. 1 and 2, fig. 1 is a system block diagram of an embodiment of a test time prediction system according to the present invention, and fig. 2 is a flowchart of a method of the embodiment of the test time prediction system of fig. 1 executing a test time prediction method. In this embodiment, the test time prediction system 100 includes: the method includes steps of a receiving module 110, a test database 120, a processing module 130, an evaluation module 140, and an output module 150 (step 210), wherein the receiving module 110 is connected to the processing module 130, the test database 120 is connected to the processing module 130, and the processing module 130 and the evaluation module 140 are respectively connected to the output module 150.
The receiving module 110, the test database 120, the processing module 130, the evaluation module 140, and the output module 150 may be implemented in various ways, including software, hardware, firmware, or any combination thereof. The techniques presented in the embodiments may be stored on a machine-readable storage medium using software or firmware, such as: read Only Memory (ROM), random Access Memory (RAM), magnetic disk storage media, optical storage media, flash memory devices, etc., and can be implemented by one or more general-purpose or special-purpose programmable microprocessors. The receiving module 110, the test database 120, the processing module 130, the evaluation module 140 and the output module 150 may be connected to each other in a wireless or wired manner for signal and data transmission.
The test database 120 stores a plurality of historical test items and corresponding test times thereof according to the test completion sequence, wherein each historical test item comprises a historical test machine model (step 220). In other words, each time any test item in the factory completes the test, the test database 120 stores the model of the test machine included in the test item and the time (i.e., the test time) taken for the test item to complete the test. The test database 120 stores the test items and the corresponding test times in the order of completion of the test (i.e., time-order).
The receiving module 110 receives a test script, where the test script includes a plurality of current test items, and each current test item includes a current test machine model and a corresponding test tool (step 230). More specifically, when a customer places an order and provides corresponding test requirements, in order to achieve various test items, a test engineer needs to input a test script on a test platform, and the receiving module 110 is configured to receive the test script input by the test engineer, wherein the test script (i.e., a test process) is divided into a plurality of test stages, each test stage includes a plurality of current test items, the current test items are tested by a plurality of node servers, and each current test item includes a current test machine model and a corresponding test tool (i.e., each current test item is tested by a node server according to the corresponding test tool).
The processing module 130 compares the similarity between the current test machine model included in each current test item and the historical test machine model included in each historical test item (step 240). More specifically, after the receiving module 110 receives the test script, the processing module 130 may disassemble the current test items included in the test script one by one, and perform similarity comparison with the historical test machine models included in each historical test item one by one based on the current test machine model included in a single current test item, so as to find the historical test machine model included in the historical test item that is closest to the current test machine model included in the current test item (in other words, perform comparison of the test machine models).
In this embodiment, each current test machine model and each historical test machine model can be classified into three classes, and respectively include a group type (group type), a family type (family type), and a model type (model type), wherein the group type is the largest class (i.e., the first class), the family type is the second largest class (i.e., the second class), and the model type is the smallest class (i.e., the third class). In other words, a single group type includes several family types, and a single family type includes several model types. The similarity comparison in step 240 may be performed sequentially according to the model type, the family type and the group type to output the corresponding similarity.
In more detail, the similarity comparison comprises the following steps: comparing the model type of the current testing machine type included in a certain current test item with the model type of the historical testing machine type included in each historical test item one by one; when the model type of the current test machine type included by the current test item is not the same as the model types of the historical test machine types included by the historical test items, comparing the family type of the current test machine type included by the current test item with the family type of the historical test machine type included by each historical test item one by one; and comparing the group type of the current test machine model included by the current test item with the group type of the historical test machine models included by each historical test item one by one when the group type of the current test machine model included by the current test item is different from the group type of the historical test machine models included by the historical test items. When the model type of the current test machine type is the same as that of the historical test machine type, the similarity between the current test machine type and the historical test machine type is highest; when the family type of the current testing machine model is the same as that of the historical testing machine model, the similarity between the current testing machine model and the historical testing machine model is the second highest; when the group type of the current testing machine model is the same as that of the historical testing machine model, the similarity between the current testing machine model and the historical testing machine model is minimum; and when the model type, family type and group type of the current test machine model are different from those of each historical test machine model, the similarity between the current test machine model and the historical test machine models is zero. Through the steps, the historical test machine model included in the historical test item closest to the current test machine model included in the current test item can be found.
Next, the processing module 130 evaluates the test time corresponding to the historical test machine model with the highest similarity to a current test machine model as the estimated time of the current test item including the current test machine model (step 250).
In this embodiment, when the similarity between a current testing machine model and each of the historical testing machine models is zero (i.e., the model type, the family type, and the group type of the current testing machine model are different from the model type, the family type, and the group type of each of the historical testing machine models, in other words, the current testing machine model is a brand-new unused testing machine model, including the current test item of the current testing machine model is a brand-new test item), the estimated time including the current test item of the current testing machine model may be the timeout time set for the current test item. The timeout set for each current test item is the maximum available time set for each current test item by the test engineer according to his experience. If the current item exceeds the predetermined time during the actual test, the current item is considered as failed, and the timeout period of the current item is used as the maximum upper limit of the estimated time of the current item.
In addition, in this embodiment, after the processing module 130 performs the similarity comparison, if there are more than two historical test items including a historical test machine type having the same similarity with a current test machine type and having the highest similarity, the processing module 130 estimates the estimated time including the current test item of the current test machine type according to the test time corresponding to the historical test item stored in the test database 120 at the latest among the historical test items. In other words, the test machine model of the plurality of test items performed in the past may be the same as or similar to the current test machine model of the current test item, and the similarity is the highest, and at this time, based on the latest historical test, the test time corresponding to the historical test item stored in the test database 120 at the latest is evaluated as the estimated time including the current test item of the current test machine model.
The evaluation module 140 evaluates the time spent by each test tool to load into the corresponding current tester model based on the speed of the network and the size of each test tool (step 260). In more detail, since the test time of the whole test script includes not only the accumulation of the estimated time for executing each current test item, but also the operation of the whole test process, it is also necessary to automatically download the test tool to the test node (i.e. the current test machine) according to the test script. Since the speed of the network and the size of the testing tool may cause the occupied time to be uncertain, in this embodiment, the evaluation module 140 may first obtain the corresponding experience estimated time in the testing process (i.e. the average time spent by each testing tool in the testing process loading to the corresponding current testing machine model) by subtracting the testing time of each testing item in the testing process from the whole testing time of each testing process in the past, and then dividing the remaining time by the number of the testing items in the testing process, and finally obtain the average consumed time of each testing tool loading to the corresponding current testing machine model in a statistical manner according to the past experience estimated times, and use the average consumed time as the time spent by each testing tool loading to the corresponding current testing machine model, but this embodiment is not intended to limit the present invention, and may be adjusted according to actual needs.
Each test tool can be, but not limited to, a validation for hardware configuration and performance check, a BT Image for representing a Linux OS system customized by a Bit Torrent (BT) protocol, a IEC STRESS for pressure test, a NIC fwup for recording firmware driver software (firmware) of hardware to a Server configuration according to a Client requirement, or a Net Server/Client for representing pairwise pairing by a plurality of node servers in a rack (rack) for network communication pressure test.
The output module 150 sums the estimated time of each current test item and the time spent by each testing tool to load to the corresponding current testing machine model to output the predicted testing time of the corresponding testing script (step 270).
Through the steps 210 to 270, the test time prediction system 100 may predict the test time item by item for the current test, and then add the time consumption weight values of other non-test items (i.e. the time spent by each test tool loading to the corresponding current test machine model) after accumulation, so as to evaluate the predicted test time with the basis of the corresponding test script.
In summary, it can be seen that the difference between the present invention and the prior art is that the processing module compares the similarity of each current test item with each historical test item stored in the test database to evaluate the estimated time of each current test item; the evaluation module evaluates the time spent by the test tool in each current test item to be loaded to the corresponding current test machine model; and the output module sums the estimated time of each current test item and the time spent by each test tool to load to the corresponding current test machine model to output the predicted test time of the corresponding test script.
Although the present invention has been described with reference to the foregoing embodiments, it should be understood that various changes and modifications can be made therein by those skilled in the art without departing from the spirit and scope of the invention.
Claims (8)
1. A test time prediction system, comprising:
the system comprises a receiving module, a testing module and a processing module, wherein the receiving module is used for receiving a testing script, the testing script comprises a plurality of current testing items, and each current testing item comprises a current testing machine type and a corresponding testing tool;
the test database is used for storing a plurality of historical test items and corresponding test time according to a test completion sequence, wherein each historical test item comprises a historical test machine model;
a processing module, configured to compare similarity between the current test machine type included in each current test item and the historical test machine type included in each historical test item, and evaluate the test time corresponding to the historical test machine type with the highest similarity to a certain current test machine type as an estimated time of the current test item including the current test machine type;
the evaluation module is used for evaluating the time spent by each testing tool to load the corresponding current testing machine model according to the speed of the network and the size of each testing tool; and
the output module is used for summing the estimated time of each current test item and the time spent by each test tool to load to the corresponding current test machine model so as to output the predicted test time corresponding to the test script.
2. The system of claim 1, wherein each current testing machine model and each historical testing machine model are classified in three levels and sequentially include a group type, and a model type, respectively, and the similarity comparison sequentially compares the model type, the group type, and the group type to output the corresponding similarity.
3. The system of claim 1, wherein the predicted time of the current item of the current test machine type is a timeout set for the current item when the similarity between the current test machine type and each of the historical test machine types is zero.
4. The system of claim 1, wherein after the similarity comparison is performed by the processing module, when the similarity between the historical test machine type included in more than two of the historical test items and a current test machine type is the same and the similarity is the highest, the processing module evaluates the test time corresponding to the historical test item stored in the test database at the latest among the historical test items as the estimated time of the current test item including the current test machine type.
5. A test time prediction method, comprising the steps of:
providing a test time prediction system which comprises a receiving module, a test database, a processing module, an evaluation module and an output module;
the test database stores a plurality of historical test items and corresponding test time according to a test completion sequence, wherein each historical test item comprises a historical test machine model;
the receiving module receives a test script, wherein the test script comprises a plurality of current test items, and each current test item comprises a current test machine model and a corresponding test tool;
the processing module compares the similarity of the current test machine type included in each current test item with the similarity of the historical test machine type included in each historical test item;
the processing module evaluates the testing time corresponding to the historical testing machine model with the highest similarity with a current testing machine model as the estimated time of the current testing item comprising the current testing machine model;
the evaluation module evaluates the time spent by each testing tool to load to the corresponding current testing machine model according to the speed of the network and the size of each testing tool; and
the output module sums the estimated time of each current test item and the time spent by each test tool to load to the corresponding current test machine model to output the predicted test time corresponding to the test script.
6. The method of claim 5, wherein each current testing machine model and each historical testing machine model are classified into three classes and sequentially include a group type, a group type and a model type, and the similarity comparison is performed sequentially according to the model type, the group type and the group type to output the corresponding similarity.
7. The test time prediction method of claim 5, further comprising: when the similarity between a current testing machine model and each historical testing machine model is zero, the estimated time of the current testing item of the current testing machine model is the set overtime time of the current testing item.
8. The test time prediction method of claim 5, further comprising: after the processing module compares the similarity, when the similarity between the historical test machine type included in more than two historical test items and a current test machine type is the same and the similarity is the highest, the processing module estimates the estimated time of the current test item including the current test machine type according to the test time corresponding to the historical test item which is stored in the test database at the latest in the historical test items.
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